AI-102 Implement computer vision solutions Practice Test 4 — 15 Questions

Question 1

Your team is building a mobile app that uses Azure AI Computer Vision to extract text from business cards. The app must handle cards in multiple languages (English, French, German). Which feature of the Computer Vision API should you use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Read API. The Read API is the correct choice because it is the current, optimized version of the Computer Vision OCR service designed specifically for extracting printed and handwritten text from images of documents, including business cards. It supports multiple languages (English, French, German) and provides a higher accuracy and structured output (lines and words with bounding boxes) compared to the legacy OCR API. The Recognize Text operation is deprecated and should not be used for new solutions.

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OCR API

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Recognize Text

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Describe Image

Question 2

You are deploying a Custom Vision object detection model to an Azure Container Instance for real-time inference. The model must respond within 500 ms. The default container runs on CPU. What should you do to meet the latency requirement?

Accepted Answer

Export the model as a Dockerfile with GPU support and deploy to a GPU-enabled ACI.. The default Custom Vision container runs on CPU, which is insufficient for real-time object detection inference within 500 ms. Exporting the model as a Dockerfile with GPU support and deploying to a GPU-enabled Azure Container Instance (ACI) leverages NVIDIA CUDA-accelerated inference, dramatically reducing latency to meet the sub-500 ms requirement.

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Increase the number of CPU cores in the container instance.

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Deploy the model to Azure Functions with a Premium plan.

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Use the Cognitive Services Computer Vision container instead.

Question 3

You need to detect if a photo contains adult or racy content. Which Azure AI Computer Vision feature should you use?

Accepted Answer

Analyze Image API with the 'adult' parameter. The Analyze Image API with the 'adult' parameter is the correct feature because it specifically detects adult, racy, and gory content in images. When you call the Analyze Image API and include the 'adult' visual feature, Azure AI Computer Vision returns a boolean flag and a confidence score for adult and racy content classification, enabling content moderation.

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Describe Image API

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OCR API

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Tag Image API

Question 4

You are using Azure AI Custom Vision to classify images of animals. The training set has 1000 images of cats and 1000 images of dogs. After training, the model performs well on the test set. However, when deployed, it misclassifies images of wolves as dogs. What is the most likely cause?

Accepted Answer

The training set does not include enough negative examples that look like dogs but are not.. The model misclassifies wolves as dogs because the training set lacks negative examples that are visually similar to dogs but belong to a different class. Custom Vision learns to distinguish classes based on the features present in the training images; without images of wolf-like canines labeled as 'not dog,' the model has no basis to reject wolves. This is a classic case of insufficient hard negative mining, where the model generalizes too broadly for the 'dog' class.

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The probability threshold is set too low.

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The model is overfitted to the training data.

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The training set has class imbalance.

Question 5

You are building a solution to analyze images of handwritten medical prescriptions. The text is in English and includes drug names and dosages. Which combination of Azure AI services should you use?

Accepted Answer

Azure AI Computer Vision Read API and Azure AI Language. The Azure AI Computer Vision Read API (part of the Image Analysis service) extracts printed and handwritten text from images, including medical prescriptions. Azure AI Language then provides entity recognition to identify drug names and dosages from the extracted text. This combination directly addresses the requirement of analyzing handwritten images and extracting structured medical information.

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Azure AI Custom Vision and Azure AI Language

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Azure AI Document Intelligence and Azure AI Language

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Azure AI Video Indexer and Azure AI Language

Question 6

Which TWO actions should you take to reduce the latency of an Azure AI Computer Vision OCR call on a large image?

Accepted Answer

Resize the image to a smaller resolution before calling the API.. Options B and D are correct. B: Resizing reduces processing time. D: Using the Read API asynchronously allows the client to poll, avoiding timeout. A: Increasing timeout doesn't reduce latency. C: Using CPU doesn't help. E: Cognitive Services container on-premises might add network latency.

Answer

Use a CPU-bound compute instance.

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Increase the API timeout value.

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Deploy the Cognitive Services container on-premises.

Question 7

Which THREE factors are critical to consider when designing a custom vision solution for a manufacturing quality inspection system?

Accepted Answer

Imbalance between defective and non-defective product samples.. Class imbalance is a critical factor in custom vision solutions for manufacturing quality inspection. If defective samples are rare compared to non-defective ones, the model may become biased toward predicting the majority class, leading to poor recall for defects. Azure Custom Vision allows adjusting the probability threshold and using techniques like oversampling or weighted loss to mitigate this, but the imbalance must be accounted for during dataset preparation.

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The need for optical character recognition (OCR) of product serial numbers.

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Multilingual support for labeling.

Question 8

Which TWO Azure AI services can be used to extract text from images?

Accepted Answer

Azure AI Document Intelligence. Azure AI Document Intelligence (formerly Form Recognizer) includes the Read OCR engine that extracts printed and handwritten text from images and documents. Azure AI Computer Vision provides the OCR API (optical character recognition) which can extract text from images, including both printed and handwritten text, and supports multiple languages. Both services are designed specifically for text extraction from visual content.

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Azure AI Face

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Azure AI Video Indexer

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Azure AI Custom Vision

Question 9

Refer to the exhibit. You run the Azure CLI command shown. What is the output?

Accepted Answer

A single key string. The `az cognitiveservices account keys list` command retrieves the access keys for an Azure Cognitive Services account. By default, it returns both key1 and key2, but the `--query` parameter with `keys[0]` filters the output to return only the first key (key1) as a single string. This is a standard Azure CLI query syntax using JMESPath to extract a specific element from the JSON response.

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Both key1 and key2

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The endpoint URL

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The region of the account

Question 10

Refer to the exhibit. You are creating an Azure Cognitive Services account using an ARM template snippet. What type of account is being created?

Accepted Answer

Azure AI Services multi-service account. The ARM template snippet uses the 'CognitiveServices' resource type and sets 'kind' to 'CognitiveServices', which provisions a multi-service account that provides access to multiple Azure AI services (e.g., Language, Computer Vision, Translator) under a single endpoint and key. This is distinct from single-service accounts, which use specific 'kind' values like 'TextAnalytics' or 'ComputerVision'.

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Azure AI Language

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Azure AI Computer Vision

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Azure OpenAI Service

Question 11

You are building a computer vision solution to detect defects on a manufacturing assembly line. The solution must process images in real-time with low latency, and you need to choose an Azure service. Which service should you use?

Accepted Answer

Azure Custom Vision. Azure Custom Vision is the correct choice because it allows you to train a custom image classification or object detection model tailored to detect specific manufacturing defects. It supports real-time, low-latency inference via a Docker container deployed to edge devices or directly through the prediction API, meeting the assembly line's performance requirements.

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Azure Computer Vision API

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Azure Video Indexer

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Azure Form Recognizer

Question 12

A retail company uses Azure Computer Vision to analyze in-store camera feeds to count customers. The solution uses the Detect API on individual frames. Recently, the counts have been inaccurate due to overlapping people. Which action should you take to improve accuracy?

Accepted Answer

Train a Custom Vision object detection model with images of crowded scenes.. The Detect API in Azure Computer Vision is a general-purpose object detection model that may not be optimized for crowded scenes with significant overlap. By training a Custom Vision object detection model with images of crowded scenes, you create a specialized model that learns to distinguish partially occluded people, improving counting accuracy. This approach leverages transfer learning to adapt the model to the specific visual patterns of your store environment.

Answer

Use the Analyze API instead of Detect API.

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Increase the confidence threshold in the Detect API call.

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Switch to Azure Video Indexer for people counting.

Question 13

You need to extract printed text from scanned invoices in multiple languages. Which Azure service should you use?

Accepted Answer

Azure Computer Vision Read API. Azure Computer Vision Read API is designed specifically for extracting printed and handwritten text from images and documents, including scanned invoices. It uses optical character recognition (OCR) to handle multiple languages, making it the correct choice for this multilingual text extraction task.

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Azure Form Recognizer

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Azure Custom Vision

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Azure Video Indexer

Question 14

A healthcare provider uses Azure Computer Vision to analyze medical images. They need to ensure patient data is not stored outside the Azure region. What should you configure?

Accepted Answer

Configure a private endpoint for the Computer Vision resource.. Configuring a private endpoint for the Computer Vision resource ensures that all traffic to the service traverses a private IP address within your virtual network, using Azure Private Link. This prevents data from being routed through the public internet and allows you to enforce data residency by keeping all data processing within the designated Azure region, as the private endpoint is deployed in the same region as your VNet.

Answer

Use the Free tier for Computer Vision.

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Enable customer-managed keys (CMK) for the Computer Vision resource.

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Deploy Computer Vision in multiple regions.

Question 15

You are designing a solution to detect brand logos in social media images. The logos vary in size and orientation. You need to achieve high accuracy with minimal false positives. Which approach should you recommend?

Accepted Answer

Train an Azure Custom Vision object detection model with labeled logo images.. Azure Custom Vision allows you to train a custom object detection model with your own labeled dataset of brand logos, enabling high accuracy for specific logo shapes, sizes, and orientations. This approach directly addresses the need for minimal false positives by learning the exact visual features of the logos, unlike generic pre-built models.

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Use Azure Computer Vision Describe API to generate captions and filter by logo mentions.

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Use Azure Computer Vision Analyze API with domain-specific models.

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Use Azure Form Recognizer to extract logo positions from images.